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Prerequistes" ], "metadata": { "id": "MNKVbDSrROWo" } }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "82KaoTcNwncw", "outputId": "c79060aa-2ec3-40dc-b262-694f2609bac9" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[K |████████████████████████████████| 86 kB 4.1 MB/s \n", "\u001b[K |████████████████████████████████| 362 kB 38.2 MB/s \n", "\u001b[K |████████████████████████████████| 81 kB 10.6 MB/s \n", "\u001b[K |████████████████████████████████| 5.1 MB 61.9 MB/s \n", "\u001b[K |████████████████████████████████| 1.1 MB 47.0 MB/s \n", "\u001b[K |████████████████████████████████| 256 kB 76.4 MB/s \n", "\u001b[K |████████████████████████████████| 2.0 MB 52.0 MB/s \n", "\u001b[K |████████████████████████████████| 54 kB 3.4 MB/s \n", "\u001b[K |████████████████████████████████| 140 kB 70.8 MB/s \n", "\u001b[K |████████████████████████████████| 84 kB 4.3 MB/s \n", "\u001b[K |████████████████████████████████| 53 kB 2.7 MB/s \n", "\u001b[K |████████████████████████████████| 212 kB 73.8 MB/s \n", "\u001b[K |████████████████████████████████| 212 kB 74.5 MB/s \n", "\u001b[K |████████████████████████████████| 596 kB 57.5 MB/s \n", "\u001b[K |████████████████████████████████| 127 kB 73.3 MB/s \n", "\u001b[K |████████████████████████████████| 4.4 MB 56.3 MB/s \n", "\u001b[K |████████████████████████████████| 43 kB 2.7 MB/s \n", "\u001b[K |████████████████████████████████| 1.2 MB 57.9 MB/s \n", "\u001b[K |████████████████████████████████| 96 kB 7.4 MB/s \n", "\u001b[K |████████████████████████████████| 6.6 MB 50.1 MB/s \n", "\u001b[K |████████████████████████████████| 144 kB 69.6 MB/s \n", "\u001b[K |████████████████████████████████| 94 kB 4.6 MB/s \n", "\u001b[K |████████████████████████████████| 271 kB 75.2 MB/s \n", "\u001b[K |████████████████████████████████| 63 kB 2.3 MB/s \n", "\u001b[K |████████████████████████████████| 80 kB 11.0 MB/s \n", "\u001b[K |████████████████████████████████| 43 kB 2.5 MB/s \n", "\u001b[K |████████████████████████████████| 62 kB 1.1 MB/s \n", "\u001b[K |████████████████████████████████| 4.0 MB 54.9 MB/s \n", "\u001b[K |████████████████████████████████| 856 kB 55.2 MB/s \n", "\u001b[K |████████████████████████████████| 58 kB 7.6 MB/s \n", "\u001b[?25h Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n", " Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n" ] } ], "source": [ "# Installing from main and specifying [\"fastai\"] to automatically install the relevant packages and versions\n", "# %%capture\n", "!pip install -Uqq huggingface_hub[\"fastai\"] gradio datasets # ohmeow-blurr \n", "# not needed just for reference:\n", "#!pip install -Uqq transformers transformers['sentencepiece'] datasets" ] }, { "cell_type": "code", "source": [ "%%capture\n", "!git clone https://github.com/ohmeow/blurr.git\n", "%cd blurr\n", "!pip install -e \".[dev]\"" ], "metadata": { "id": "x8hYHGkp08D2" }, "execution_count": 6, "outputs": [] }, { "cell_type": "code", "source": [ "import torch\n", "import datasets\n", "import transformers\n", "from fastai.text.all import *\n", "\n", "from blurr.text.data.all import *\n", "from blurr.text.modeling.all import *" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "cd73fba0cb46455580a55f00c24c474a", "71fbe36f932640ba97d5f2061813d3b5", "4790b536b7cd4b8fb2b6adee54437b53", "4319d9a8636e4fc8996f113c11a59787", "3499a49996714418a1bb5ddbd0e5488f", "41703df5fdb64afbb7732337193654bd", "410f8b5bb68240878ee0e06d06dac7b9", "6e22c95dd34346cf89847fb33dff55c6", "7fbf0d651e04429e98be4596623a5cc5", "2b21969ed1124cc7ab7755723478b2ef", "fde33665d5704c2081bbfd7f5a1984cf", "25839133a7f74536aad30dfcc829cfbe", "945ae30ecfde4a59a09e1b2bb0a2e4ff", "f7c70bf68eb04b8fad221d3935ec1cfb", "2d382495b0bf43548ee64093d2a7b2d7", "9cad5d2f258b4147a92782b64ffa16d8", "dd54838fe45847dfa7c22710a6ed2ba3", "c843095ff5a14698a0a51c082f3c8db1", "272b04be4cfb4512b8beabc136a273d1", "f46598268aa3486d80334accaad1446f", "bcf0f63d4dd64ce1ab3880f38833d5af", "3a42e9dcbeaf49e9937549bc64e0ca9e" ] }, "id": "cZNvReXYxWBZ", "outputId": "8d605830-aa1a-4375-8e6e-0ba774ab58dc" }, "execution_count": 4, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/1.72k [00:00 of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ " 0%| | 0/4800 [00:00\n", "
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textlabelbusinessentertainmentsportstechnologyis_valid
0ഉപഗ്രഹങ്ങളുടെ കൂട്ട വിക്ഷേപണത്തിലൂടെ കഴിഞ്ഞ സാമ്പത്തിക വർഷം വൻ നേട്ടം കൊയ്ത് ഐഎസ്ആർഒ . ഐഎസ്ആർഒയുടെ വിശ്വസ്ത ലോഞ്ചിംഗ് വെഹിക്കിളായ പിഎസ്എൽവി ഇതുവരെ 28 രാജ്യങ്ങളിൽ നിന്നുള്ള 209 ഉപഗ്രഹങ്ങളാണ് ബഹിരാകാശത്ത് എത്തിച്ചത് . ഇതുവഴി ഐഎസ്ആർ വൻ സാമ്പത്തിക നേട്ടമുണ്ടാക്കിയതായി കണക്കുകൾ പറയുന്നു . ഐഎസ്ആർഒയുടെ വാണിജ്യ വിഭാഗമായ ആൻട്രിക്സിലൂടെ വിദേശ രാജ്യങ്ങളുടെ വാണിജ്യ ഉപഗ്രഹങ്ങൾ വിക്ഷേപിച്ച് 2015 - 2016 സാമ്പത്തികവർഷം 230 കോടി രൂപയാണ് ഐഎസ്ആർഒ സ്വന്തമാക്കിയത് . 2013 - മുതൽ 2015 വരെയുള്ള രണ്ടുവർഷ കാലയളവിൽ 28 വിദേശ ഉപഗ്രഹങ്ങൾ വിക്ഷേപിച്ചതുവഴി ആൻട്രിക്സ് 600 കോടി രൂപയുടെ ആകെ നേട്ടമുണ്ടാക്കിയിരുന്നു . ഈ വർഷം ...30001False
1വിവിധ തിയ്യേറ്ററുകളിൽ മോഹൻലാൽ ചിത്രം ഒടിയന്റെ ആദ്യ പ്രദർശനം തുടങ്ങി . ഹർത്താലിന്റെ പശ്ചാത്തലത്തിൽ ആഘോഷങ്ങൾ കുറവാണെങ്കിലും തിയ്യേറ്റർ ഹൌസ്ഫുള്ളാണ് . 37 രാജ്യങ്ങളിലായി 3500 കേന്ദ്രങ്ങളിലായിരുന്ന റിലീസ് . എന്നാൽ ഹർത്താലിന്റെ പശ്ചാത്തലത്തിൽ ചില തിയ്യേറ്ററുകളിലെ ഷോ മാറ്റിവച്ചു . സുരക്ഷാ പ്രശ്നമുള്ളതിനാൽ വൈകീട്ട് ആറ് മണിക്ക് ശേഷം ചിത്രം പ്രദർശിപ്പിക്കും . ചിലയിടങ്ങളിൽ പ്രദർശനം നിർത്തിവച്ചിട്ടുണ്ട് . പ്രദർശനം നടക്കാത്തതിലുള്ള അമർശവും ചില ആരാധകർ ഏഷ്യാനെറ്റ് ന്യൂസിനോട് പങ്കുവച്ചു . ഇന്നലെ രാത്രി വരെ അന്വേഷിച്ചപ്പോൾ ഷോ പ്രദർശനം നടക്കുമെന്ന് അറിയിച്ചിട്ടാണ് എത്തിയതെന്നും ആരാധകർ പറഞ്ഞു . എന്നാൽ പൊലീസ്...10100False
2ഇന്ത്യക്കെതിരായ ഏകദിന പരമ്പരയ്ക്കുള്ള ടീമിനെ ഇന്ന് രാവിലെയാണ് ക്രിക്കറ്റ് ഓസ്ട്രേലിയ പ്രഖ്യാപിച്ചത് . പേസർ പീറ്റർ സിഡിൽ , സ്പിന്നർ നഥാൻ ലിയോൺ , മുൻനിര ബാറ്റ്സ്മാൻ ഉസ്മാൻ ഖവാജ എന്നിവർ ടീമിൽ തിരിച്ചെത്തിയപ്പോൾ മിച്ചൽ സ്റ്റാർക്ക് , ജോഷ് ഹേസൽവുഡ് , പാറ്റ് കമ്മിൺസ് എന്നിവർക്ക് വിശ്രമം അനുവദിച്ചിരുന്നു . ഇന്ത്യയെ നേരിടാൻ ഈ ടീം മതിയോ എന്ന സംശയം ടീം പ്രഖ്യാപനത്തിന് പിന്നാലെ വിവിധ കോണുകളിൽ ഉയർന്നിരുന്നു . ഇപ്പോഴിതാ ക്രിക്കറ്റ് ഓസ്ട്രേലിയയുടെ ടീം സെലക്ഷനെതിരെ പരസ്യമായി പ്രതികരിച്ച് ഇതിഹാസ താരം ഷെയ്ൻ വോൺ രംഗത്തെത്തി . ലോകകപ്പ് പോരാട്ടം പടിവാതിൽക്കൽ എത്തി നിൽക്കെയുള്ള ക്രിക്കറ്റ് ഓസ്ട്രേലിയയുടെ ടീം സെ...20010False
3സംസ്കൃതത്തിൽ ഗജമെന്നാൽ ആനയെന്നാണ് അർഥം . തമിഴ്നാട്ടിൽ അതിരാമപട്ടണത്തിന് പടിഞ്ഞാറ് മണിക്കൂറിൽ 95 കിലോമീറ്റർ വേഗത്തിൽ വീശിയടിച്ച ചുഴലിക്കാറ്റിന് പേരിട്ടത് ശ്രീലങ്കയാണ് . ആനയുടെ ശക്തിയുള്ള കാറ്റ് എന്ന അർഥത്തിൽ . ഗജ വെള്ളിയാഴ്ച മൂന്നു മണിയോടെ ന്യൂനമർദമായി മാറി കേരള തീരത്തിലെത്തി ഇടുക്കി , പാലക്കാട് ജില്ലകളിലൂടെ കേരളം കടന്ന് അറബിക്കടലിലേക്ക് നീങ്ങി . വെള്ളിയാഴ്ചയും ശനിയാഴ്ചയും ചില ജില്ലകളിൽ ഇതിന്റെ ഭാഗമായി ശക്തമായ മഴ ഉണ്ടാകുമെന്ന് കാലാവസ്ഥാ നിരീക്ഷണ കേന്ദ്രം പറയുന്നു . ഒഡീഷ തീരത്ത് വീശിയ തിത്ലി ചുഴലിക്കാറ്റിനുശേഷം ഗജ എത്തുമ്പോൾ പേരുകളിലെ വ്യത്യസ്തതയാണ് ആദ്യം ശ്രദ്ധിക്കപ്പെടുന്നത് . ചുഴലിക്കാറ്റ...30001False
4ആപ്പിൾ ഡ്രൈവർ ആവശ്യമില്ലാത്ത കാറുകൾ നിർമ്മിക്കാൻ ഒരുങ്ങുന്നു . ആപ്പിൾ മേധാവി ടിം കുക്ക് തന്നെയാണ് ഈ കാര്യം വ്യക്തമാക്കിയത് . ബ്ലൂബെർഗിന് നൽകിയ അഭിമുഖത്തിലാണ് ടെക് ഭീമൻറെ വെളിപ്പെടുത്തൽ . ജൂൺ 5 ന് പ്രസിദ്ധീകരിച്ച അഭിമുഖത്തിൽ ഓട്ടോണമസ് ഓട്ടോമൊബൈൽ രംഗത്തേക്ക് ആപ്പിൾ ഉടൻ കടന്നുവരും എന്നാണ് ടിംകുക്ക് പറയുന്നത് . എങ്ങനെയിരിക്കും പ്രോഡക്ട് എന്നോ , പദ്ധതി എങ്ങനെയിരിക്കും എന്നോ ഇപ്പോൾ വ്യക്തമാക്കുവാൻ സാധിക്കില്ല . എന്നാൽ ഞങ്ങൾ അത് ചെയ്തിരിക്കും . ഇത് ഒരു കേന്ദ്രീകൃതമായ സാങ്കേതികതയിൽ അടിസ്ഥിതമായിരിക്കുമെന്നും ടിം കുക്ക് പുതിയ ടെക്നോളജിയെക്കുറിച്ച് സൂചന നൽകുന്നു . കഴിഞ്ഞ ഏപ്രിലിൽ ആപ്പിൾ തങ്ങളുടെ ഓട്ട...30001False
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\n", " \n", " " ] }, "metadata": {}, "execution_count": 12 } ] }, { "cell_type": "markdown", "source": [ "# 3. Using Blurr High Level API" ], "metadata": { "id": "b2zEkYMt8Q_K" } }, { "cell_type": "code", "source": [ "lbl_cols = raw_datasets['train'].features[\"label\"].names\n", "lbl_cols" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "641Ualhk9FYH", "outputId": "6c9f23e0-afcf-4642-e23f-2da3149f60f3" }, "execution_count": 13, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "['business', 'entertainment', 'sports', 'technology']" ] }, "metadata": {}, "execution_count": 13 } ] }, { "cell_type": "code", "source": [ "from transformers import AutoConfig, AutoModelForSequenceClassification\n", "model_cls = AutoModelForSequenceClassification\n", "\n", "pretrained_model_name = \"xlm-roberta-base\"\n", "config = AutoConfig.from_pretrained(pretrained_model_name)\n", "config.num_labels = len(lbl_cols)\n", "\n", "hf_arch, hf_config, hf_tokenizer, hf_model = get_hf_objects(pretrained_model_name, model_cls=model_cls, config=config)\n", "hf_model.config.problem_type = \"multi_label_classification\"\n", "\n", "print(hf_arch)\n", "print(type(hf_config))\n", "print(type(hf_tokenizer))\n", "print(type(hf_model))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 214, "referenced_widgets": [ "8ea70b256992431cba00cf30cc9e5011", "4ab09f5e583b4498872f6390c257d8f5", "2213dde6d62e4580bfee0bf08df0e4f1", "d49f1787887a4910a0d7aa033a986e1f", "736411a65a4344ff928ab36ff0cd3ae1", "666202f9a7604d33866f57960e04ef02", "a3c4cb5ef07e4b92ba09a12c5d838410", "802c74d385ee4901947373e9b28e6530", "e6034bbb32cd4a65947d9b96288e09d6", "8b48a37a95c44770be3ec2261351baa4", "5ae7b6246d2a4e29826e9430cfd465a9", "f781bc57bafd4e76a3315833fb160d26", "c9117fa79bf8415497753d04366b66fc", "e2f83d5d01ec470f8b301d68b356ebd8", "74e1e21e31084a1e9fc145b5aa381e67", "f4ffc1d34662458184299545891193e3", "714d4b45454a433fb2d67e76b3a05e30", "ef48d4b61d2f451cb43baf4fa06bcc1f", "b875358eb30f4e19bb26b58814ea3bac", "2017ea0adef34a5a9194391ecf6f8b57", "74c086e754cb4d66bf551e6af4bc0013", "caae20f08047412996a1ae2c3f95ce13", "3d2ab18a2a5a4df487c81abd72717934", "1b8d03a513cc4746a8916438f69153c9", "4aad3609ef49478486abed55eb99e8a6", "7b6c560ac54d44de8651542bbb01872e", "1003c075bee04c3789d5bf2c98accc4a", "04680c253f6f4cc08aba9d012158f3df", "89fcc45b59be4178b3f785a4188aa70b", "7f2b9b80ae2b4a14be456981066de6df", "343ecd3e539c4136bdae5397522e89a3", "2895b181d76341329de2694274f69323", "54e4d8635daa453cac663b97dbb13780", "d774487d10f346e18ff29e1e3abbefce", "b89c9a1524364eceb15d144ccd683d00", "6733f229f8d34357a7156c4293237851", "8054196720c345bc80ba97d86e6d2bbe", "4228fcb5d6a8478f82c0b74076e1e431", "2508fa5b3aa445319630f8a0bc8ead66", "1c34e59a43fc4192940054404a288af2", "c74633815aea47f6a912b62b09bfea51", "e1d7fe7a734041a88a4d902743437382", "165ea8868d764896879db41e500b1f43", "5d247630d540470c9274692f94b67f13" ] }, "id": "hG3RjxnX8vJn", "outputId": "97ec2a8c-a3db-4889-e0b8-a387aa24a7d5" }, "execution_count": 14, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading: 0%| | 0.00/615 [00:00\n", "\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "learn = BlearnerForSequenceClassification.from_data(\n", " mlnews_df, pretrained_model_name, text_attr=\"text\", label_attr=lbl_cols, dl_kwargs={\"bs\": 4}\n", ")\n", "\n", "learn.loss_func.thresh = 0.02" ], "metadata": { "id": "8arnjjmXyTp7" }, "execution_count": 15, "outputs": [] }, { "cell_type": "code", "source": [ "learn.fit_one_cycle(1, lr_max=1e-2)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81 }, "id": "JCX9ooCl-kJ2", "outputId": "8029c0b1-1b91-4396-9dc4-c9240aa6f6a2" }, "execution_count": 16, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "\n" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
epochtrain_lossvalid_lossf1_scoreaccuracy_multitime
00.5955740.5709420.0000000.75000000:48
" ] }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "learn.loss_func.thresh = 0.01\n", "\n", "comment = \"\"\"\n", "2032 ഒളിമ്പിക്‌സിന് ബ്രിസ്‌ബെയ്ന്‍ വേദിയാകും; ഗെയിംസിന് വേദിയാകുന്ന മൂന്നാമത്തെ ഓസ്‌ട്രേലിയന്‍ നഗരം\n", "\"\"\"\n", "learn.predict(comment)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "nBwaBS_CAOG8", "outputId": "aa0a9d18-d41e-451e-af55-31d2fb1c3ca9" }, "execution_count": 17, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "[{'class_indices': [1, 1, 1, 1],\n", " 'class_labels': ['business', 'entertainment', 'sports', 'technology'],\n", " 'labels': ['business', 'entertainment', 'sports', 'technology'],\n", " 'probs': [0.3053056001663208,\n", " 0.1699194461107254,\n", " 0.2217995971441269,\n", " 0.26829949021339417],\n", " 'scores': [0.3053056001663208,\n", " 0.1699194461107254,\n", " 0.2217995971441269,\n", " 0.26829949021339417]}]" ] }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "markdown", "source": [ "# 5. Share in Huggingface" ], "metadata": { "id": "eFg2LWCERbe1" } }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "notebook_login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 387, "referenced_widgets": [ "66bb0fd2486d473e8c80181d2ccb69f2", "2766c9d92cca4b60a9000d06652b609f", "ce7cc6aca4d045d2b506fb45bca7e25f", "16ff2c34a20a4fa59be465c1ec656742", "ba0c151e3dcd4a0881ecc1383e0f2c69", "1d4f75973a0e4bbf81a3809414b1c8a1", "58b785915e184f6a9f1b9007092e8cf2", "b0c26fb626df4aba8b9bbebb8dcb7f09", "1c339fe6bac44bc09d396c863792d516", "c52f2fb712314e7b8aa6cd74debb09e5", "2f326ab34071486fb0cc464f0816b68a", "42d3aee7e0f846daa7f231d67e7a9f40", "a96b94fc595547f08e1539d45cb07490", "bb43bccf7cc74d6582405ffef899a21d", "74493812f31a4eb8be6195da828f6235", "35bc22a979144e8991b9aa05124e3612", "016befa05b5845ee9c5c1d790ab7081b" ] }, "id": "NOxscWweye1T", "outputId": "b8e9dedc-bab7-4b66-abe6-45e7fcad775b" }, "execution_count": 18, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Login successful\n", "Your token has been saved to /root/.huggingface/token\n", "\u001b[1m\u001b[31mAuthenticated through git-credential store but this isn't the helper defined on your machine.\n", "You might have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal in case you want to set this credential helper as the default\n", "\n", "git config --global credential.helper store\u001b[0m\n" ] } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import push_to_hub_fastai\n", "\n", "push_to_hub_fastai(learner=learn, repo_id=repo_id)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 154, "referenced_widgets": [ "8f526bd535cb4169af3d0b184ea32493", "cdc6688ee917408a92c6195aad962626", "c16c3b54d81f485f88c688db27d30942", "986208015fb74113b246ea41d4b6c937", "e51c7702e13147f1b24fd77495e9b855", "8392f3626fd649538b8f0ec7e2a123a6", "de9b384c62104ca2b780ecdb2fd7f0e0", "cd6fd071060c49259b234c0d548cf635", "024047803f60491987f178c5141fb569", "b0d3ed3b1ea24313900312d546acca5e", "fb0d2cc0c64f49f791e03d0cd0f4f584" ] }, "id": "keAmGvH5zowe", "outputId": "15d3c30d-7d2d-4eb8-b105-ce3bb70c877f" }, "execution_count": 19, "outputs": [ { "metadata": { "tags": null }, "name": "stderr", "output_type": "stream", "text": [ "Cloning https://huggingface.co/hugginglearners/ml-news-classify-fastai into local empty directory.\n", "Adding files tracked by Git LFS: ['model.pkl']. This may take a bit of time if the files are large.\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8f526bd535cb4169af3d0b184ea32493", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Upload file model.pkl: 0%| | 3.33k/1.04G [00:00 main\n", "\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "'https://huggingface.co/hugginglearners/ml-news-classify-fastai/commit/28ab382cf93d199f434c5445221dfad2b8f3172a'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 19 } ] }, { "cell_type": "markdown", "source": [ "# 6. Loading a Learner from the Hugging Face Hub" ], "metadata": { "id": "7rce2KDE0cxo" } }, { "cell_type": "code", "source": [ "from huggingface_hub import from_pretrained_fastai\n", "# ഞാൻ ചിന്തിക്കുന്ന കുറച്ചു ആശയങ്ങൾ പ്രാവർത്തികം ആക്കുക എന്നുള്ളതാണ്\n", "# ഇതുവരെ ഞാൻ കണ്ടുമുട്ടിയതും പരിചയവുമുള്ള സോഫ്റ്റ്‌വെയർ സേവനങ്ങൾ \n", "# എങ്ങനെ പ്രയോജനപ്പെടുത്താം എന്നുള്ള വിവരങ്ങൾ ഇവിടെ പരിചയ പെടുത്തുന്നതുമാണ്. \n", "learner = from_pretrained_fastai(repo_id)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 145, "referenced_widgets": [ "f8070b34faf549b98bb45f253fbbf8aa", "76b6156862d04b1ba7dac077a9b09e95", "b80411897e824e23ac915d5bd7d9f878", "f6286467e03b4ba7a7232b5eaf0653c3", "b8efed684c4245648b44403141a4692d", "b1c13e388f504c36a51b0cb9c03eb75d", "7f5ad04da0c942e6a9e7747580f9fd2c", "e3aec685ba2b473a8f80c95e5ab35b90", "b5baf4382cd0458fb1e190c5dba09d97", "47c77a56223643448775e39369c7b1bd", "1fa9a722c7d9497e9deb2d4492c22add", "cc35fa2eec134914903b4ba8e5f39150", "97172b8d76b44460aebb5d2b2446cf6b", "b14bd9277fd64e77abdc22e16f89be4b", "b1559618adda41aa864958356b7f5383", "0d42e3809be04d9788716a8c21406f4c", "b6ab593019d54ebdbae791f1982e58ab", "a2b357ab94b44edebc6a12096864e499", "d587698e4f6d41c9814e27da013039e7", "f3f5760db9f5452d99138b2e20d5ab6e", "1f357b5192cc4865802645defa7f6c89", "1bc989b6984049d5851a6df43762ee2b", "ae89f623a7b241b1adaa0d3b0780f29c", "772a643c30fd44d5b4ce6cc70fe2b658", "dc72059cb26f413f9ea5cd334342dc6b", "df88178e82c54a3abcd68d7d874d3531", "0294a40484be4b9ebaba025493494310", "9652c3ed20ec42cc980c4d8a576d76e0", "9f2935d46821448eba0b81e10c0900a0", "849c3ee3d6f3491ab78d095ba1463d61", "02c59f553a7944e5828f2bdb28f39c71", "d6fc7ae28cbf4754897ccc0e09af5341", "e586d71e811d4bb3955b3797de8a6a40", "425bd06cfe534fd9be8c41a6edf5a467", "fe841f48dac34ed78e2089be81917dbb", "4763295a23a747ccb1c72388fbb45745", "5ce95e4076b3420cb53cf899de06703a", "a0a76a46d6624885b051a7b342ddded2", "a60d5a2434734861a30c38a0029877ec", "89d84fb4af494363976edf9c526231d4", "521645d081634acdbf8dc82dec5987b8", "23bd1fedd74c42c89305642fe76b2002", "4356d54754a94614a49cdcb16dc213e2", "d0214621d30b46d1aac2bab22d2f3694" ] }, "id": "-Jcd8dC10b4s", "outputId": "2e206ca8-1a67-4d89-ad74-c846bff918e7" }, "execution_count": 13, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading: 0%| | 0.00/1.22k [00:00Malayalam News Classifier | Demo Model

\",\n", " examples=[[\"ഓഹരി വിപണി തകരുമ്പോള്‍ നിക്ഷേപം എങ്ങനെ സുരക്ഷിതമാക്കാം\"], [\"വാര്‍ണറുടെ ഒറ്റക്കയ്യന്‍ ക്യാച്ചില്‍ അമ്പരന്ന് ക്രിക്കറ്റ് ലോകം\"]],\n", " # live=True,\n", " # share=True\n", " )\n", "interface.launch(debug=True)\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 695 }, "id": "dUEja_m-wk46", "outputId": "81db548e-eb82-4662-9810-b2ea84445465" }, "execution_count": 7, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.7/dist-packages/gradio/interface.py:286: UserWarning: Currently, only the 'default' theme is supported.\n", " warnings.warn(\"Currently, only the 'default' theme is supported.\")\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n", "Running on public URL: https://45332.gradio.app\n", "\n", "This share link expires in 72 hours. For free permanent hosting, check out Spaces (https://huggingface.co/spaces)\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
" ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Keyboard interruption in main thread... closing server.\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "(,\n", " 'http://127.0.0.1:7860/',\n", " 'https://45332.gradio.app')" ] }, "metadata": {}, "execution_count": 7 } ] }, { "cell_type": "code", "source": [ "# \"spaces/rajeshradhakrishnan/malayalam-news-classify\"\n", "gr.Interface.load(\"spaces/hugginglearners/malayalam-news-classify\").launch(debug=True) " ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 345 }, "id": "0uqXDtLPjj_E", "outputId": "3420d227-a4d0-4c83-f15d-5d007db658a3" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Fetching interface from: https://huggingface.co/spaces/hugginglearners/malayalam-news-classify\n" ] }, { "output_type": "error", "ename": "TypeError", "evalue": "ignored", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# \"spaces/rajeshradhakrishnan/malayalam-news-classify\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"spaces/hugginglearners/malayalam-news-classify\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/gradio/interface.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(cls, name, src, api_key, alias, **kwargs)\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mgradio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0ma\u001b[0m \u001b[0mGradio\u001b[0m \u001b[0mInterface\u001b[0m \u001b[0mobject\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 89\u001b[0m \"\"\"\n\u001b[0;32m---> 90\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msrc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mapi_key\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mapi_key\u001b[0m\u001b[0;34m,\u001b[0m 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